Specialist – Data scientist
Frances Tyson
‘I am recognised as a leader in my specialist field. I am committed to building specialist capability in the ATO, establishing broad networks and utilising my skills to support the future client experience.’
I was headhunted by the ATO for my unique expertise in analytics. I was attracted to the idea of working with the ATO and being able to use real time data to understand and respond to changes in taxpayer behaviour and circumstances.
As a data scientist, I had developed complex models using predictive data mining software. It proved valuable in my previous role within a large organisation, so I saw the benefit of applying it in the ATO. Knowing how the ATO valued innovative practices, I engaged senior leaders to highlight the opportunity to use the models to improve our work practices.
My colleagues realised the potential of these models immediately. I easily loaded them onto the ATO’s analytic collaboration environment which enabled me to run advanced algorithms on the ATO’s high performance systems, which was exciting.
I connected with the ATO’s multidisciplinary analytics community through my digital profile. From there I was able to work with specialists in different fields to test the models on real taxpayer data in a secure environment. Together we enhanced the models to better understand behavioural patterns of taxpayers, gather evidence and identify emerging risks to the tax and super systems. This allowed the ATO to provide a better experience for taxpayers by adjusting interactions based on behavioural patterns.
We’ve been able to use taxpayer data to pre-fill and tailor tax returns. We’ve also used the data from business software to provide small business with current benchmarks against industry standards to determine their business viability. This means we are improving our service to taxpayers and I feel that I have contributed to a broader agenda to minimise red tape.
Acknowledging the benefits of collaborating, I connected with my international peers to create a multi-skilled team which included our counterparts in other Australian Government agencies. Together we exchanged real time data and shared technical insights. As a result of our collaboration, we identified behavioural and transactional trends across international boundaries. We realised that we were able to use the data models to develop risk strategies and mitigate impacts to the revenue system.
Working on projects like this has demonstrated my expert skills as a leader in the data science field. I have learnt a lot from working in a team of data scientists, technicians, miners and analysts in the ATO. I was able to build capability within the ATO by transferring knowledge to this team of specialists. I shared our tools and techniques with other government agencies and international jurisdictions. This has opened up a global network of specialists for us to work with in the future.
How the ATO behaves
- We take a global view – looking across the ATO, government and internationally.
- We identify future trends and are ready to respond.
- We are open to new ways and new thinking.
- We willingly share information, insights and experience locally and internally.
- We use our skills and expertise to help clients do the right thing.
What the ATO does
- Frances identifies and engages the right experts to achieve outcomes for the ATO, contributing to the broader agenda.
- We invest in tools and technology to support Frances in her specialist work.
- We recognise and enhance Frances’ expertise by enabling mobility opportunities.
- We promote and support Frances’ development, accreditation and networks.
- We support short distinct engagements enabling differentiation of specialist job design and employment contracts.
How the ATO supports clients
- We have a complete view of our taxpayers, creating greater community confidence and trust in our dealings as a professional revenue agency.
- We tailor our engagements to proactively assist and collaborate with our clients across the ATO, government and internationally.